Distribution metrics

Statistical property metrics measured on the entity level are divided according to data entity format type:

Metric	Categorical	Numeric	Boolean
Distribution shift	✔	✔	✔
Top frequent percents Frequency of the mode value.	✔	-	-
Unique values The number of unique values.	✔	-	-
Entropy Calculation of the entropy on the distribution of categorical entities.	✔	-	-
Min value The lowest value.	-	✔	-
Max value The highest value.	-	✔	-
Sum value The sum of values.	-	✔	-
Mean value The average value.	-	✔	-
Standard Deviation The measure of the amount of variation in a numeric entity.	-	✔	-
Proportion Percent of positive value.	-	-	✔

Feature Importance

Superwise measures the effect a feature has on a model. Superwise calculates feature importance using SHAP values during version creation, using a reference dataset, or you can set this manually while configuring the schema.

Distribution shift & drift metrics:

Distribution shift
How different the distribution in the selected data is from the reference dataset over time. The scale ranges from 0-100, where 0 indicates identical distribution, and 100 indicates orthogonal distribution.
Input drift
The average distribution shifts across all features.